Abstract
In the epoch of the Internet of Things (IoT), we have confronted five challenges (Connectivity, Value, Security, Telepresence, and Intelligence) with complex structures. The IoT industry decision making is critically important for countries or societies to enhance the effectiveness and validity of leadership, which can greatly accelerate the industrialized and large-scale development. In the case of IoT industry decision evaluation, the essential problem arises serious incompleteness, impreciseness, subjectivity, and incertitude. Interval neutrosophic set, disposing of the indeterminacy portrayed by truth membership T, indeterminacy membership I, and falsity membership F with interval form, is a more viable and effective means to seize indeterminacy. The main purpose of this paper is to investigate the multiparametric distance measure and similarity measure. Meanwhile, some interesting properties of distance measure and similarity measure are proved. Then, the objective weights of diverse attributes are ascertained by the deviation-based method. Moreover, we explore the combination weight, which reveals both the objective preference and subjective preference. The validity of the algorithm is illustrated by an IoT industry decision-making issue, along with the effect of diverse parameters on the ranking. Finally, a comparison of the developed with the existing interval neutrosophic decision-making methods have been executed in the light of the counter-intuitive phenomena and unauthentic issue for displaying their effectiveness.
Highlights
The Internet of Things (IoT) is deemed to an economic and technology wave of global information industry after the Computer and Internet
For counting the distance measure and similarity measure of two interval neutrosophic sets (INSs), we introduce a novel way to build the distance measure and similarity measure which depend on three parameters, namely, t1, t2 and p, where p is the Lp norm, t1, t2 identify the level of uncertainty
The proposed model is different from the existing interval neutrosophic weight determining approaches, which can be classed as two sides: (1) subjective weighting determine approaches and (2) the objective weighting determining approaches, which can be calculated by bran-new deviation-based method
Summary
The Internet of Things (IoT) is deemed to an economic and technology wave of global information industry after the Computer and Internet. Peng and Dai [33] presented three MADM methods based on MABAC, similarity measure and EDAS. Bolturk and Kahraman [38] developed the interval-valued neutrosophic method based on AHP with cosine similarity measure. The goal of this paper is to deal the above issue by proposing a new similarity measure method for INS, which can have without above problems. The proposed model is different from the existing interval neutrosophic weight determining approaches, which can be classed as two sides: (1) subjective weighting determine approaches and (2) the objective weighting determining approaches, which can be calculated by bran-new deviation-based method.
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